Woman looking at data
© Laurence Dutton / Getty Images

Predictive analytics and BMI misrepresentation


The U.S. life insurance marketplace is evolving rapidly toward automation and smarter allocation of resources to provide a better experience for policy holders and issuers. Many insurers are implementing various approaches for accelerated underwriting where a subset of applications for fully-underwritten products qualify to have their medical exams and fluid testing waived.

Without medical exams and verification of disclosures, applicants know their disclosures will not be verified, and it becomes easy to misrepresent health status and obtain a better underwriting class. Body mass index (BMI) is an important driver of risk class and stands as the second largest concern for misrepresentation in accelerated underwriting after smoking non-disclosure. BMI misrepresentation occurs when the BMI as measured by a medical professional differs from the BMI self-reported by the applicant, typically in the direction of the applicant underreporting the true BMI. With research confirming BMI misrepresentation rates of 20% or higher in fully underwritten programs, these rates are expected to increase in accelerated programs, imposing a material impact on mortality risk.

This article by Munich Re Life US summarizes the extra mortality impact from BMI misrepresentation, Munich Re’s approach to modelling misrepresentation, and how these models can be used to better manage mortality risk in accelerated underwriting programs.

Contact the author
Malika Shahrawat
Malika Shahrawat
Data Scientist
Integrated Analytics